The invention relates to digital data processing and more particularly, by way of non-limiting example, to the automated generation of user interfaces that are customized to individual behaviors. The invention has application, by way of non-limiting example, in e-commerce web sites and e-commerce software apps, among others.
Just as in its brick-and-mortar counterpart, browsing is key to e-commerce sales. Most consumers who visit a retailer have a general idea of what they are looking for. Some may even know the particular model/style, color, size and so forth. But few, if any, know the precise aisle/shelf (in the case of brick-and-mortar retail) or web page (in the case of web retail) whence to find an item for purchase.
Brick-and-mortar retailers take advantage of this by placing items so that a consumer who is walking store aisles for a given offering, say, Levi's 505 jeans, can see related offerings by that same maker (501's, etc.), along with those of competitors. And, while placement is often by product type (jeans vs khakis vs cords, etc.), it can also be by make (Levi's vs Wrangler vs Lee, etc.).
Web retailers struggle with this. There is, as yet, no impactful web equivalent to walking up and down aisles “just looking for something” a/k/a browsing. While software applications known as browsers are ubiquitous on web-ready consumer devices, they might better be known as “searchers,” since that is their main function. This might not have been the case in the early days of the web, when users were accustomed to finding items of interest by following category links of the type provided in Yahoo!'s hierarchical directory. However, keyword searching is now the norm, and unless web retailers pre-sort search results or supplement them with “you might also be interested in” links, the consumer is likely to come up short or overwhelmed and, in any case, frustrated.
Web retailers are trying to combat this by monitoring search strings as they are being entered by site visitors and automatically completing them with keyword search predictions that will produce “hits” on the site. For example, a user who visits the website of a clothing retailer and types the characters “je” into the search box might be presented with one, or both, of the auto-completion search predictions “jeans” and “jerseys,” depending on which, or both, categories of clothing the retailer actually carries.
Another strategy web retailers employ is to customize search results according to visitors' individual profiles. For example, a visitor that has previously purchased Levi's jeans from a given retail site, might be presented with that maker's offerings over those of other makers in response to a non-specific search for jeans; whereas another visitor to the same site who enters that same search request might be shown Wrangler jeans first in search results, if that is the maker from whom that visitor previously bought such articles.
This is becoming increasingly difficult, however, as web retailing comes to the fore and the number of web consumers rises. The demands on retail web site storage, processing power and other resources necessary to support customization is fast becoming unmanageable.
In view of the foregoing, an object of the invention is to provide improved methods and apparatus for digital data processing and more particularly, by way of non-limiting example, for automated generation of customized user interfaces.
A further object of the invention is to provide such methods and apparatus as are suited for web browsing, e.g., in connection with web retailing.
A further related aspect of the invention is to provide such methods and apparatus as are suited for the generation of search results and/or search suggestions that are personalized for each user.
These and other objects of the invention are evident in the drawings and in the discussion that follows.